Point it at a company's Glassdoor Jobs or Overview page and get that employer's whole open-roles board back as rows: the job title, the location, the posted salary range, how old the posting is, whether it takes Easy Apply, and a link to each listing. Sorted by relevance or newest first, your choice.
The input is the employer, not the job - you name the companies and the run collects every role they currently have listed.
One row per role, each tagged with the query it came from - so a run across thirty employers still reconciles back to your input list.
A keyword search returns whoever ranked for it. This takes the company and returns everything that company is advertising, which is the difference between a sample and a census of one employer's hiring.
Glassdoor is Cloudflare-protected, which is why a hand-rolled script on an office IP tends to come back with an interstitial rather than jobs. Residential routing, rate limiting and IP rotation happen on our side; from yours it is a form or an API call.
Choose Most relevant or Newest First and cap the rows per query up front, so credits go on the slice you actually want. The rank Glassdoor returned is kept in every export, so you can re-sort without losing it.
Each row carries the posting as Glassdoor's company jobs board shows it: the title, the employer, the location, the salary range where one is published, how old the listing is, the Easy Apply marker and a link to the job.
Titles come back verbatim, capitalisation and all, exactly as the employer wrote them. The column list below is the header row of real runs rather than a specification - and the parts worth your attention are which columns arrived empty on every row, and the fact that date_posted is an age rather than a date. Both are spelled out rather than left to be discovered.
Taken from the header row of real runs. Our testing covered a single employer, so read the column notes as that company’s postings rather than as behaviour guaranteed across employers.
City, ST with a two-letter US state code, though some rows carry the bare string United States instead. Filled on every row, just not always to city level.(Employer provided), (Glassdoor est.) and (Glassdoor Est.) — note the two casings of est., so match it case-insensitively. Not a number.24h, 3d, 9d and so on up to 30d+, which is a ceiling rather than a measurement. Filled on every row.Yes when the posting takes Easy Apply, and an empty cell otherwise. No never appeared - absence is the negative.Four things to know before you write code against this. First, date_posted holds an age - 24h, 9d, 30d+ - and not a date; anything that parses it as one will fail on every row, and 30d+ is a ceiling that cannot tell you whether a posting is 31 days old or 300. Second, company_rating, snippet and logo were empty on every row of every run, so plan for them as empty rather than as data you can filter on. Third, salary is a formatted string rather than a number, its bracketed source varies in case between (Glassdoor Est.) and (Glassdoor est.), and the unit follows the domain you queried - K on glassdoor.com, Indian lakh L on glassdoor.co.in. Fourth, all twelve columns are present in the CSV and XLSX as well as the JSON; there is no format here that carries fewer.
Sort order and a per-query limit decide what a run costs and what lands in the file. Both are chosen before the job starts, alongside how you hand over the list of companies.
A few examples of how teams use company-scoped hiring data to answer a question they actually have.
What a company hires for is what it is about to build. Pull a rival's whole board and the titles tell you where headcount is going - a run of platform and data roles reads differently from a run of enterprise sales ones.
Export the boards of everyone you compete with for talent and compare the published ranges side by side. The salary column marks whether each figure came from the employer or from Glassdoor's estimate, so you can weight them differently.
A company staffing up a function is a company about to spend on it. Watch a target list's boards on a schedule and treat a burst of new postings in one department as the trigger for outreach.
No subscription, no minimum, no recurring bill. Your first 500 rows are on us - after that, pay-as-you-go at the same flat rate as every other scraper here.
Every new account, one-time. No credit card required. Sorting, per-query limits, file upload and every export format included.
Roughly $2 per 1,000 jobs. The pre-flight estimator shows the row count and credit cost before a run starts - no surprise bills, no compute units to translate.
Volume pricing, dedicated workers and an SLA for continuous monitoring or very large historical pulls. Tell us your numbers and we will quote.
LIVESCRAPER10 at checkout.The employee side of the same question - rating, headline, pros, cons and whether staff would recommend the place. An open role reads differently next to what the people already there wrote.
The firmographics behind the board - industry, size band, exact headcount, headquarters and website - so twenty open roles can be read against how big the company already is.
Short answer: yes for the public listing content - and this export carries nothing about any individual person.
Job listings on Glassdoor are published to be found. The title, the location, the posted salary range, the age of the listing and the link are shown to anyone who opens the company's jobs page, signed in or not. Collecting publicly visible job postings for labour-market research is long-established practice, and nothing here touches a login, an application or a paywall.
There is no person anywhere in this output. No recruiter, no hiring manager, no applicant, no reviewer - the columns describe a role and the employer advertising it. That makes a hiring study built on this data a study of companies rather than of people, which is a meaningfully different position to be in than with a reviews or profiles export.
Glassdoor's own terms restrict automated access, so this is a terms question as well as a legal one - if you have a contractual relationship with the site, check it. We run no third-party trackers on the data layer, and your exports auto-delete after 30 days.
The questions we hear most. Anything else? Talk to us - humans, not bots, write the answers.
500 one-time free rows on every new account - no expiry. After that it is $0.002 per row, pay-as-you-go - no card on file until you say so.
Livescraper's Glassdoor Company Jobs Scraper turns a list of employers into hiring data. You submit Glassdoor company URLs - a Jobs page or an Overview page, typed one per line or uploaded as a CSV, XLSX, TXT or Parquet file - choose whether the roles come back by relevance or newest first, cap the rows per query if you want to, and download the board as a clean CSV, Excel or JSON file.
Each row carries the posting as Glassdoor's company jobs board shows it: the title exactly as the employer wrote it, the location, the published salary range where there is one, how old the listing is, the Easy Apply marker, a permalink to the job and the rank Glassdoor gave it within your query. All twelve columns appear in every export format, so a spreadsheet loses nothing next to the JSON.
Strategy teams read a competitor's whole board because what a company hires for is what it is about to build. Compensation teams export the boards of everyone they compete with for talent and compare published ranges, weighting employer-provided figures differently from Glassdoor estimates. Sales teams watch a target list on a schedule and treat a burst of postings in one department as a buying signal.
Two properties of this dataset matter before you build on it. The date_posted column holds an age - 24h, 9d, 30d+ - rather than a date, and 30d+ is a ceiling that cannot distinguish a month-old posting from a year-old one. And company_rating, snippet and logo did not carry values in our testing, so plan for them as empty rather than as filters. Start free: your first 500 rows cost nothing and need no credit card, and after that it is $0.002 per row, flat.